Toxic Relationships Described by People With Breast Cancer on Reddit: Topic Modeling Study
Bibliographic record
Abstract
BACKGROUND: Social support is essential to promoting optimal health outcomes for women with breast cancer. However, an estimated 12% of women with breast cancer simultaneously experience intimate partner violence (IPV; physical, psychological, or sexual abuse by an intimate partner). Women who experience IPV during breast cancer may lack traditional social support, and thus seek out alternative sources of support. Online community forums, such as Reddit, can provide accessible social connections within breast cancer-specific communities. However, it is largely unknown how women with breast cancer use Reddit to describe and seek support for experiences of IPV. OBJECTIVE: This study aims to explore how patients with breast cancer describe toxic relationships with their partners and immediate family members on Reddit. METHODS: This exploratory, cross-sectional, topic-modeling study analyzed textual data from 96 users in the r/breastcancer subreddit in February 2023. The meaning extraction method, inclusive of principal component analysis, was used to identify underlying components. Components were subjected to sentiment analysis and summative content analysis with emergent categorical development to articulate themes. RESULTS: Seven themes emerged related to toxic relationships: (1) contextualizing storytelling with lymph nodes, (2) toxic behavior and venting emotions, (3) abandonment and abuse following diagnosis, (4) toxic relationships and social-related fears, (5) inner strength and navigating breast cancer over time, (6) assessing social relationships and interactions, and (7) community advice and support. Toxic relationships were commonly characterized by isolation, abandonment, and emotional abuse, which had profound emotional consequences for patients. Reddit facilitated anonymous venting about toxic relationships that helped patients cope with intense feelings and stress. Exchanging advice and support about navigating toxic relationships during breast cancer were core functions of the r/breastcancer community. CONCLUSIONS: Findings emphasized the value of Reddit as a source of social support for patients with breast cancer experiencing toxic relationships. Clinicians who understand that many patients with breast cancer experience toxic relationships and considerable psychological sequelae are better prepared to support their patients' holistic well-being. Further investigation of Reddit as a possible resource for advice, information, and support has the potential to help inform clinical practice and subsequently, patient health outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".